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Eric Newkirk
Eric Newkirk

Wildlife Research and Species Conservation Data Analyst

Areas of Interest and Expertise


I strive to develop tools to help wildlife researchers and managers interact with their data more seamlessly, integrating multiple types of data from various sources and incorporating modern technologies to help turn data into answers as accurately and efficiently as possible.

More Specifically

I’ve been involved in a wide variety of wildlife research projects for more than 15 years, and have always felt driven to find ways to make those projects work better for both the teams in the field and the supervisors in the office. To that end I began creating more modern and sophisticated data management solutions for many of those projects, in order to streamline the processes of data collection, entry, and analysis. My experience in the field and specialized skillset give me a unique perspective on the problems managers and researchers face in the era of big data and how best to solve them. I specialize in SQL Server, Microsoft Access, and R, but I also dabble in a handful of other programming languages and platforms, and more recently I’ve been focusing on making machine learning tools more accessible to those who study wildlife.


CPW Photo Warehouse

Select Publications

  • S Kraberger et al. 2021. Complex evolutionary history of felid anelloviruses. Virology 562:176-189.
  • RA Bandoo et al. 2021. Identification of novel circovirus and anelloviruses from wolverines using a noninvasive faecal sampling approach. Infection, Genetics and Evolution 93:104914.
  • MA Tabak et al. 2020. Improving the accessibility and transferability of machine learning algorithms for identification of animals in camera trap images: MLWIC2. Ecology and Evolution 10:10374-10383.
  • CR Shores, JA Dellinger, ES Newkirk, SM Kachel, and AJ Wirsing. 2019. Mesopredators change temporal activity in response to a recolonizing apex predator. Behavioral Ecology arz080.
  • MA Tabak et al. 2019. Machine learning to classify animal species in camera trap images: Applications in Ecology. Methods in Ecology and Evolution 10:585-590.
  • S Kraberger et al. 2018. Identification of circular single-stranded DNA viruses in faecal samples of Canada lynx, moose, and snowshoe hare inhabiting the Colorado San Juan Mountains. Infection, Genetics and Evolution 64:1-8.
  • JS Ivan, AE Seglund, RL Truex, and ES Newkirk. 2018. Mammalian responses to changed forest conditions resulting from bark beetle outbreaks in the Southern Rockies. Ecosphere 9(8): e02369.
  • JS Ivan and ES Newkirk. 2016. CPW Photo Warehouse: a custom database to facilitate archiving, identifying, summarizing, and managing photo data collected from camera traps. Methods in Ecology and Evolution 7:499-504.


B.S., Molecular Environmental Biology, University of California, 2001

Current or Recent Positions

  • Research and Species Conservation Data Analyst – Colorado Parks and Wildlife, 2022-Present
  • Database Administrator/Programmer – Speedgoat Wildlife Solutions, 2019-2022
  • Field Technician/Data Analyst – Colorado Parks and Wildlife, 2011-2018